Multi-tissue platform for modeling systemic pathologies In our current UH2/UH3 grant, we have established an exceptionally strong scientific premise for developing a multi-tissue platform for modeling disease and testing drug safety and efficacy. We propose to establish a functional network of five tissue systems: heart, liver, skin, bone and vasculature, all grown from the same batch of iPS cells, and perfused with a blood substitute containing circulating immune cells. We have already achieved unprecedented levels of maturity and physiologic function for these tissue systems. A key innovation in the proposal is in the biomimetic approach to functional integration, by (i) maintaining a local regulatory niche for each tissue, (ii) connecting tissue units by a common perfusate containing immune cells, and (iii) establishing endothelial barrier between the vascular and tissue compartments. The platform will be modular, configurable, PDMS-free and featuring real-time monitoring of cell and tissue functions. Another innovative component is in the integrated systems biology approach to the analysis of complex data sets in disease modeling. We hypothesize that the matured tissues in our platform connected by vascular flow can replicate the drug-induced, multi-organ, transcriptional, metabolic, and functional changes observed in patients. To test this hypothesis and validate the platform, we will investigate the widespread off-target effects of doxorubicin, the drug used to treat most human cancers. In the initial UG3 phase of the project, our goal is to validate the model by comparing tissue responses in the platform to those measured clinically. Aim 1 is to develop a configurable multi-tissue platform with vascular perfusion and immune cells. Aim 2 is to characterize the five interacting tissue systems, and demonstrate stable tissue phenotypes over 4 weeks of culture. Aim 3, representing a transient to UH3 phase of the project, is to demonstrate utility of the integrated disease model. In the UH3 phase of Aim 3, we will recapitulate high susceptibility to doxorubicin of patients with dilated cardiomyopathy, and study the disease and population diversity. Aim 4 is to evaluate drug delivery modalities, risk factors and cell-protective agents. Machine-learning algorithms will be developed for cross-validation and synthesis of comprehensive data generated in the platform. Aim 5 is to characterize the multi-tissue models of disease using a systems biology/bioengineering approach. Our overall goal is to deliver a commercial-ready platform formed from a single source of iPS cells, and demonstrate its value for predictive, patient-specific modeling of disease.